Multi-Objective Energy-Efficient Interval Scheduling in Hybrid Flow Shop Using Imperialist Competitive Algorithm

Zhou, Rui; Lei, Deming; Zhou, Xiaojian

doi:10.1109/access.2019.2924998

Cited by 22 publications

(11 citation statements)

References 53 publications

(81 reference statements)

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“…In addition, the main contributions of this paper compared to related papers [32][33][34][35][36][37][38][39][40][41][42][43][44][45], are as follows:…”

Section: Discussionmentioning

confidence: 99%

“…Currently, there is an increasing number of publications about EES [16][17][18][19][20][21][22]. Different models of machine energy consumptions processes [14] and all shop floor types have been investigated in the literature, such as single machine scheduling [23][24][25][26][27], flow shop [28][29][30][31][32][33][34][35][36][37][38][39][40][41], job shop [42][43][44][45][46][47], and hybrid systems for specific issues [48][49][50]. For many machine tools, the idling power consumption is only slightly less than the operating power consumption [51].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times

Kampa

Paprocka

2021

Energies

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The aim of this paper is to present a model of energy efficient scheduling for series production systems during operation, including setup and shutdown activities. The flow shop system together with setup, shutdown times and energy consumption are considered. Production tasks enter the system with exponentially distributed interarrival times and are carried out according to the times assumed as predefined. Tasks arriving from one waiting queue are handled in the order set by the Multi Objective Immune Algorithm. Tasks are stored in a finite-capacity buffer if machines are busy, or setup activities are being performed. Whenever a production system is idle, machines are stopped according to shutdown times in order to save energy. A machine requires setup time before executing the first batch of jobs after the idle time. Scientists agree that turning off an idle machine is a common measure that is appropriate for all types of workshops, but usually requires more steps, such as setup and shutdown. Literature analysis shows that there is a research gap regarding multi-objective algorithms, as minimizing energy consumption is not the only factor affecting the total manufacturing cost—there are other factors, such as late delivery cost or early delivery cost with additional storage cost, which make the optimization of the total cost of the production process more complicated. Another goal is to develop previous scheduling algorithms and research framework for energy efficient scheduling. The impact of the input data on the production system performance and energy consumption for series production is investigated in serial, parallel or serial–parallel flows. Parallel flow of upcoming tasks achieves minimum values of makespan criterion. Serial and serial–parallel flows of arriving tasks ensure minimum cost of energy consumption. Parallel flow of arriving tasks ensures minimum values of the costs of tardiness or premature execution. Parallel flow or serial–parallel flow of incoming tasks allows one to implement schedules with tasks that are not delayed.

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“…In addition, the main contributions of this paper compared to related papers [32][33][34][35][36][37][38][39][40][41][42][43][44][45], are as follows:…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times

Kampa

Paprocka

2021

Energies

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“…Many scholars have studied the EES flow shop model. In particular, Zhou et al [24] proposed an energy-efficient model of hybrid flow shop to solve interval scheduling problem. Liu et al [25] proposed a new mixed integer programming model for energy-efficient integration of process planning and scheduling.…”

Section: Model Of Energy-efficient Schedulingmentioning

confidence: 99%

A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat

et al. 2020

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This paper aims to solve the problem of high energy consumption in forging production through energy-saving scheduling. By analyzing the flow shop characteristics of a forging workshop, an energy-efficient hybrid flow shop scheduling problem with forging tempering (EEHFSP-FT) is proposed. An energy-efficient scheduling model is established to simultaneously minimize both the completion time and energy consumption. In the scheduling model, constraints such as heating furnace capacity, required forging temperature, and required quenching temperature are taken into consideration. An energy-saving strategy of heat treatment with residual forging heat is adopted to address the problem of energy underutilization after forging. In order to use multi-objective optimization algorithms to solve the scheduling problems of charging and machine selection in forging production, encoding and decoding rules and evolutionary search strategies are designed. Finally, a case study on the flow shop of an automated forging center is analyzed. The validity of the proposed model is demonstrated by testing cases of different scales in conjunction with three different evolutionary algorithms. By analyzing the performance of the three algorithms, the algorithm suitable for solving the proposed model is determined. INDEX TERMS Energy saving scheduling; Forging planning; Multi-objective optimization; Temperature constraint.

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“…The detailed process is shown in Fig.7. jobs removed [3,5] All possible sub-solutions of the first restoration Retain the best one [1,2,4,5,3,6] The new solution Considering the different search performance of different memeplexes, some memeplexes do not participate in memeplex shuffling. Memeplexes with good performance are directly retained, while memeplexes with poor performance will be shuffled.…”

Section: ) Igmentioning

confidence: 99%

“…Shen et al [4] designed a modified teaching-learning-based optimisation algorithm for bi-objective re-entrant HFSP. Zhou et al [5] provided an imperialist competitive algorithm to solve multi-objective energy-efficient interval scheduling in HFSP. Lei et al [6] presented a novel teaching-learning-based optimization algorithm for energy-efficient HFSP.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Distributed Hybrid Flow Shop Scheduling Problem With Heterogeneous Factory and Unrelated Parallel Machine: A Shuffled Frog Leaping Algorithm With Collaboration of Multiple Search Strategies

Wang

2020

IEEE Access

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The single factory production is shifting to multi-factory production which brings new challenges. Hybrid flow shop problem (HFSP) as a common problem in production-manufacturing has been studied extensively, however distributed hybrid flow shop problem (DHFSP) has not been paying sufficient attention. Fuzzy distributed hybrid flow shop problem (FDHFSP) is studied and a shuffled frog leaping algorithm with collaboration of multiple search strategies (SFLA-CMSS) is proposed to optimize multiple objectives simultaneously. In SFLA-CMSS, multiple search-mode collaboration strategy in memeplex search consists of multiple search strategies. A search strategy is selected according to the historical search status of the solution. Dynamic memeplex number adjustment strategy is used to provide more search opportunity to the memeplex which has better search capability. Experiments are conducted and the computational results reveal that SFLA-CMSS has promising advantages on FDHFSP. INDEX TERMS hybrid flow shop; distributed scheduling, heterogeneous factory; unrelated parallel machine; fuzzy scheduling; shuffled frog leaping algorithm

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Multi-Objective Energy-Efficient Interval Scheduling in Hybrid Flow Shop Using Imperialist Competitive Algorithm

Cited by 22 publications

References 53 publications

Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times

Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times

A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat

Fuzzy Distributed Hybrid Flow Shop Scheduling Problem With Heterogeneous Factory and Unrelated Parallel Machine: A Shuffled Frog Leaping Algorithm With Collaboration of Multiple Search Strategies

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